Kongu Engineering College

About: Kongu Engineering College is a based out in . It is known for research contribution in the topics: Computer science & Cluster analysis. The organization has 2001 authors who have published 1978 publications receiving 16923 citations.

Synthesis and Characterization of Mesoporous, Nanostructured Zinc Aluminium Carbonate Layered Double Hydroxides (ZAC-LDHs) and Its Calcined Product (CZA-LDH)

Abstract: In the present study, Zinc Aluminium Carbonate Layered Double Hydroxides (ZAC-LDHs) with hydrotalcite like material are synthesized at different Zn2+/Al3+ molar ratios (R = 2:1, 3:1 & 4:1) by co-precipitation followed by hydrothermal method using cationic surfactant Cetyl Trimethyl Ammonium Bromide (CTAB) as a soft template at constant pH 9. The Calcined Zinc Aluminium Carbonate LDH (CZA-LDH) sample is prepared by calcination of Zn3Al Carbonate-LDH at 450 °C for about 2 h. The materials obtained ZAC-LDHs (R = 2, 3 & 4) and calcined sample (CZA-LDH) are characterized by a set of powder X-Ray Diffraction (PXRD), N2 adsorption and desorption isotherms (Brunauer–Emmett–Teller BET), Fourier Transform Infrared Spectroscopy, Field Emission Scanning Electron Microscope with Energy Dispersive Spectroscopy (FESEM with EDS), Thermogravimetric Analysis (TGA and DTA) and high Resolution Transmission Electron Microscope (HR-TEM). The increase in intensity and sharpness of the peak from the XRD pattern confirms that all the synthesized materials of ZAC-LDHs (R = 2, 3 & 4) are crystalline in nature. Owing to more advantageous property called “memory effect”, the CZA-LDH reconstruct its original LDH structure by intercalating anions present in aqueous solution. From the XRD and BET surface analysis of data, the formation of mesoporous and nano structured crystalline material of ZAC-LDHs and CZA-LDH through simple and synergistic methods of co-precipitation and hydrothermal method at 120 °C using CTAB as a soft template is confirmed.

Production of lactic acid from industrial waste paper sludge using Rhizopus oryzae MTCC5384 by simultaneous saccharification and fermentation

Abstract: Petrochemical plastics have become a basic requisite in today’s world. Their production has increased dramatically since the last few decades owing to the increase in their demand. Sustainable gree...

Cationic Dyes Sequestration from Aqueous Phase Using Biosurfactant Based Reverse Micelles

Abstract: Several conventional methods are employed to remove cationic dyes from waste water. A novel technique based on liquid/liquid extraction using reverse micelles is proposed whereby recovery of solvent and reuse of dye is possible. Single component batch experimental studies were carried out using two dyes, namely Basic red 9 (BR9) and basic violet 3 (BV3). Glycolipids produced naturally using Pseudozyma antarctica from soybean oil medium were used as surfactant. Extraction efficiency of single component system of each dye was investigated by using amyl alcohol as solvent and sulphuric acid as carrier. The process parameters such as dye concentration, sulphuric acid concentration and surfactant concentration on the extraction efficiency were optimized using Box-Behnken design. The optimum conditions were calculated by using Derringer’s desirably.

Wind profile prediction using a Meta-cognitive Fully Complex-valued neural network

Abstract: This paper applies the recently developed Meta-cognitive Fully Complex-valued Radial Basis Function (Mc-FCRBF) network for predicting the speed and direction of wind. Mc-FCRBF network contains two components: a cognitive component and a meta-cognitive component. A Fully Complex-valued Radial Basis Function (FC-RBF) network is the cognitive component and a self-regulatory learning mechanism is its meta-cognitive component. In each epoch of the training, when the sample is presented to the Mc-FCRBF network, the meta-cognitive component decides what to learn, when to learn, and how to learn based on the knowledge acquired by the FC-RBF network and the new information contained in the sample. Performance comparison of the meta-cognitive fully complex-valued RBF network (Mc-FCRBF) applied for wind speed prediction shows better prediction of wind profile (Speed) characteristics when compared to a real-valued extreme learning machine and FC-RBF network.

Remote Sensing Analysis of Agricultural Drone

Abstract: Farmers have more requirements for the completion of cultivations. Remote sensing is a big technology for reducing this requirement. Now, we need an organic spraying system at a low cost. We have two methods, first one neural network algorithm of quantum geographic information system (QGIS) and another one global positioning system (GPS) with drone. This paper describes the analysis of drone remote sensing using the normalized difference vegetation index (NDVI)/Near-infrared band (NIR) sensor in a multispectral view of agricultural land. NIR and NDVI images had water content values and precision values which is mixed in managing water resources. NDVI sensors are loaded to produce high-density images. Real-time monitoring coupled in NIR imaging geometrically and radiometrically adjusted to measure temperature. Multispectral and hyperspectral views had used for analyzing the tested data. Standard irrigation level is 60% to produce the plant growing. Irrigation techniques followed the treatment of the plant within continuous data per second. The implemented view focused only on growth controlling of plant in-depth irrigation between 30 and 90 cm in 60% deviation. NDVI, green normalized difference vegetation index (GNDVI), soil brightness index (SBI), green vegetation index (GVI), degree of yellow vegetation index (YVI), nitrogen sufficiency index (NSI), perpendicular vegetation index (PVI), transformed vegetation index (TVI), soil adjusted vegetation index (SAVI) and vegetation condition index (VCI) vegetation indices are used to the correlation of plant growth control with managing leaf strength and import python packages display the Vegetation various Real-time value in QGIS. Correlation of plant growth p ≤0.01, r = 0.77 and − 0.77 with conductance. It measured degree and demonstrated GPS view using irrigation techniques to control water stress. It had used to estimate the leaf conductance rate with the variation of atmospherically changing. It can calculate real-time leaf stress analysis. This report provided a drone survey analysis of compost percentage and vegetation indices of agricultural land.